Plugins

Reports Docker CLI, context, and daemon reachability in WSL, plus vLLM :8000 /v1/models health and GPU runtime hints.

Image generation workbench and agent tool for DSH: one tool (ark9_generate_image) paints text-to-image and image-to-image via any OpenAI-compatible API. Channels are entirely user-configured - no bundled endpoint, you bring your own baseURL, key and model name (manual input supported). Agent-initiated generations are approval-gated by default: requests queue in the floating panel and nothing bills until you approve; approval is non-blocking (the agent replies "awaiting your approval" immediately, and results, denials or timeouts are injected back so the agent reports them in the next turn). Floating glass workbench with five tabs (Generate / Approvals / Prompts / History / About), aspect-ratio grid with quality-budget + 16px-alignment sizing, transparent background, batch up to 10 images as aggregated sub-tasks, prompt library with custom JSON sources fetched through a host proxy, persistent generation logs with one-click retry, multi-channel aggregation with per-channel model fetching, bilingual UI (zh/en), stroke-SVG icon set, config import/export. Registers as a Better Sidebar tab when dsh-better-sidebar is installed; stacks above the dsh-cua FAB when both are present.

Three independent language channels for model output — tool-call descriptions (every tool-call card title, including run_code in PTC-style presets), thinking, and replies — each set to follow the web GUI language, force a specific language, or turn off (default: only descriptions, following the GUI). One global runtime-context prompt directive on the host; the client half reports the GUI language; a Settings plugin card switches the modes.

Floating GPU monitor for the DSH Web UI: a compact, draggable strip with one row per discrete GPU (exact name, utilization, VRAM, temperature, power draw) from nvidia-smi, stays visible over side panels and side cards, with a top-VRAM-process list when the driver reports it; degrades to an n/a pill on machines without an NVIDIA driver.

Slash commands ported from other coding agents (setup, connect, install, trust, browse, doctor, status, model, memory, compact, resume, review, mcp, init, suggest, improve, refactor), a zero-dependency static scanner for plugin source, and an in-repo catalog of audited plugin report cards that cite file-and-line evidence.

Runs a parallel code review squad of read-only reviewer subagents (security, correctness, tests, style), each optionally on its own model, and aggregates one severity-grouped report from /review or a code_review tool call.

Uses a GitHub App to report open PRs and the latest Actions run for the current repo without returning secrets.

Reports the current WSL distro and warns about multi-distro setups.

Parses DSH session logs to attribute AI-written files, overlays c8 coverage, and reports AI vs human code coverage with a trust score, plus a check/fix/verify tool loop for closing test gaps.

Neural Ledger · 神经账本 — turn your DSH collaboration sessions into a visual work ledger: token analytics, smart insights, trend forecasting, and one-click daily/weekly/monthly Markdown reports.

DeepSeek-Harness plugin for multi-model orchestration with recursive task decomposition, dynamic routing, quality gates, failure recovery, and KPI reporting.

Read-only DSH environment health check: disk, memory, latency, ~/.dsh bloat and outdated-plugin detection with graded reports and baseline trend comparison. Deletes nothing.

A plugin for dsh: monitor the resource utilization of dsh system processes, and report the results to the user in the form of charts.

DeepSeek Harness plugin for NI Multisim circuit generation, simulation, optimization, and lab reports via MCP

Structured machine-readable CI output for DeepSeek Harness: JSON/NDJSON session reports, JUnit XML, semantic exit codes, artifact collection and privacy redaction - a dsh profile bundle plus a standalone CLI.

Multi-agent dashboard skill for DeepSeek Harness -- status reports, task tracking, progress visualization

Applies structured unified diffs (git format) to the real filesystem: multi-file/hunk parsing, fuzzy hunk location with line-offset correction, all-or-nothing application with typed conflict reports, reverse-patch undo journal and dry-run - four patch_* dsh tools plus a CLI.

Personal bookkeeping for DeepSeek Harness: record expenses/income (single or batch), list, monthly/annual stats with trends, budgets with progress/over-limit alerts, soft-delete restore, CSV & self-contained HTML report. Zero deps, local JSON. 个人记账插件

Scans the DSH loader tree at startup for plugin conflicts (duplicate mounts, failed or pending plugins, duplicate config row ids), auto-stops or restores the affected plugins, and shows a conflict report popup in the web UI.

Read-only health clinic for the installed DSH plugin set: loader health, dependency integrity, version compatibility, install-script risk, duplicates and patch integrity, delivered as a model tool, a Settings dashboard and JSON reports.

Automatic type-check diagnostics: after the model edits or creates TS files, runs `tsc --noEmit` in the background (debounced per project) and reports errors via the `code_check` tool — grouped by file with line/column, severity and TS error codes, closing the "edit → check → fix" loop.

Reports bounded, repository-relative Git status as structured data without staging, committing, or changing branches.

Deep-collaboration writing agent for DSH: per-user writing-style learning from edit pairs, clarify→outline→section-writing→red-team→reader-gallery flow, project-to-report synthesis (lab report / product intro / survey / README), 41 MCP tools, and web selection-improve UI with in-app file preview.